R Notebook

Load libraries

library(knitr)
library(rmdformats)

Registered S3 methods overwritten by 'htmltools':
  method               from         
  print.html           tools:rstudio
  print.shiny.tag      tools:rstudio
  print.shiny.tag.list tools:rstudio

library(ggplot2)
library(ggpubr)
library(GGally)

Registered S3 method overwritten by 'GGally':
  method from   
  +.gg   ggplot2

library(car)

Loading required package: carData

library(tidyverse)
library(lme4)
library(lmerTest)
library("MuMIn")
library(lmtest)
library(boot)

Read dataset

AllSubs_NeuralActivation <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_clean.csv')

AllSubs_NeuralActivation_Comedy <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_Comedy_clean.csv')

AllSubs_NeuralActivation_Horror <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_Horror_clean.csv')

Notes:

• Have note removed outliers from data.

Create data frames for each model.

# Define aggregate variables. 
All_Gross_W1_log <- log(AllSubs_NeuralActivation$Gross_US_W1_num)
All_Theaters_W1 <- AllSubs_NeuralActivation$Theaters_US_W1_num

Comedy_Gross_W1_log <- log(AllSubs_NeuralActivation_Comedy$Gross_US_W1_num)
Comedy_Theaters_W1 <- AllSubs_NeuralActivation_Comedy$Theaters_US_W1_num

Horror_Gross_W1_log <- log(AllSubs_NeuralActivation_Horror$Gross_US_W1_num)
Horror_Theaters_W1 <- AllSubs_NeuralActivation_Horror$Theaters_US_W1_num
  
M1_df <- data.frame(All_Gross_W1_log, All_Theaters_W1) 
M1_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_Theaters_W1) 
M1_H_df <- data.frame(Horror_Gross_W1_log, Horror_Theaters_W1) 

# Define affect variables.
All_PA <- AllSubs_NeuralActivation$Pos_arousal_scaled
All_NA <- AllSubs_NeuralActivation$Neg_arousal_scaled

Comedy_PA <- AllSubs_NeuralActivation_Comedy$Pos_arousal_scaled
Comedy_NA <- AllSubs_NeuralActivation_Comedy$Neg_arousal_scaled

Horror_PA <- AllSubs_NeuralActivation_Horror$Pos_arousal_scaled
Horror_NA <- AllSubs_NeuralActivation_Horror$Neg_arousal_scaled

M2_df <- data.frame(All_Gross_W1_log, All_PA, All_NA) 
M2_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA) 
M2_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA) 

# Define ISC variables. 
All_NAcc_ISC <- AllSubs_NeuralActivation$NAcc_ISC
All_AIns_ISC <- AllSubs_NeuralActivation$AIns_ISC
All_MPFC_ISC <- AllSubs_NeuralActivation$MPFC_ISC

Comedy_NAcc_ISC <- AllSubs_NeuralActivation_Comedy$NAcc_ISC
Comedy_AIns_ISC <- AllSubs_NeuralActivation_Comedy$AIns_ISC
Comedy_MPFC_ISC <- AllSubs_NeuralActivation_Comedy$MPFC_ISC

Horror_NAcc_ISC <- AllSubs_NeuralActivation_Horror$NAcc_ISC
Horror_AIns_ISC <- AllSubs_NeuralActivation_Horror$AIns_ISC
Horror_MPFC_ISC <- AllSubs_NeuralActivation_Horror$MPFC_ISC

# Define models. 
M4_df <- data.frame(All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
M4_C_df <- data.frame(Comedy_NAcc_ISC, Comedy_AIns_ISC, Comedy_MPFC_ISC) 
M4_H_df <- data.frame(Horror_NAcc_ISC, Horror_AIns_ISC, Horror_MPFC_ISC) 

M5_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
M5_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_ISC, Comedy_AIns_ISC, Comedy_MPFC_ISC) 
M5_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_ISC, Horror_AIns_ISC, Horror_MPFC_ISC) 

# Define whole variables. 
All_NAcc_whole <- AllSubs_NeuralActivation$NAcc_whole
All_AIns_whole <- AllSubs_NeuralActivation$AIns_whole
All_MPFC_whole <- AllSubs_NeuralActivation$MPFC_whole

Comedy_NAcc_whole <- AllSubs_NeuralActivation_Comedy$NAcc_whole
Comedy_AIns_whole <- AllSubs_NeuralActivation_Comedy$AIns_whole
Comedy_MPFC_whole <- AllSubs_NeuralActivation_Comedy$MPFC_whole

Horror_NAcc_whole <- AllSubs_NeuralActivation_Horror$NAcc_whole
Horror_AIns_whole <- AllSubs_NeuralActivation_Horror$AIns_whole
Horror_MPFC_whole <- AllSubs_NeuralActivation_Horror$MPFC_whole

# Define models. 
M6_df <- data.frame(All_NAcc_whole, All_AIns_whole, All_MPFC_whole) 
M6_C_df <- data.frame(Comedy_NAcc_whole, Comedy_AIns_whole, Comedy_MPFC_whole) 
M6_H_df <- data.frame(Horror_NAcc_whole, Horror_AIns_whole, Horror_MPFC_whole) 

M7_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_whole, All_AIns_whole, All_MPFC_whole) 
M7_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_whole,
                      Comedy_AIns_whole, Comedy_MPFC_whole) 
M7_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_whole,
                      Horror_AIns_whole, Horror_MPFC_whole) 

# Define onset variables. 
All_NAcc_onset <- AllSubs_NeuralActivation$NAcc_onset
All_AIns_onset <- AllSubs_NeuralActivation$AIns_onset
All_MPFC_onset <- AllSubs_NeuralActivation$MPFC_onset

Comedy_NAcc_onset <- AllSubs_NeuralActivation_Comedy$NAcc_onset
Comedy_AIns_onset <- AllSubs_NeuralActivation_Comedy$AIns_onset
Comedy_MPFC_onset <- AllSubs_NeuralActivation_Comedy$MPFC_onset

Horror_NAcc_onset <- AllSubs_NeuralActivation_Horror$NAcc_onset
Horror_AIns_onset <- AllSubs_NeuralActivation_Horror$AIns_onset
Horror_MPFC_onset <- AllSubs_NeuralActivation_Horror$MPFC_onset

# Define models. 
M8_df <- data.frame(All_NAcc_onset, All_AIns_onset, All_MPFC_onset) 
M8_C_df <- data.frame(Comedy_NAcc_onset, Comedy_AIns_onset, Comedy_MPFC_onset) 
M8_H_df <- data.frame(Horror_NAcc_onset, Horror_AIns_onset, Horror_MPFC_onset) 

M9_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_onset, All_MPFC_onset) 
M9_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_onset,
                      Comedy_AIns_onset, Comedy_MPFC_onset) 
M9_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_onset,
                      Horror_AIns_onset, Horror_MPFC_onset) 

# Define middle variables. 
All_NAcc_middle <- AllSubs_NeuralActivation$NAcc_middle
All_AIns_middle <- AllSubs_NeuralActivation$AIns_middle
All_MPFC_middle <- AllSubs_NeuralActivation$MPFC_middle

Comedy_NAcc_middle <- AllSubs_NeuralActivation_Comedy$NAcc_middle
Comedy_AIns_middle <- AllSubs_NeuralActivation_Comedy$AIns_middle
Comedy_MPFC_middle <- AllSubs_NeuralActivation_Comedy$MPFC_middle

Horror_NAcc_middle <- AllSubs_NeuralActivation_Horror$NAcc_middle
Horror_AIns_middle <- AllSubs_NeuralActivation_Horror$AIns_middle
Horror_MPFC_middle <- AllSubs_NeuralActivation_Horror$MPFC_middle

# Define models. 
M10_df <- data.frame(All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
M10_C_df <- data.frame(Comedy_NAcc_middle, Comedy_AIns_middle, Comedy_MPFC_middle) 
M10_H_df <- data.frame(Horror_NAcc_middle, Horror_AIns_middle, Horror_MPFC_middle) 

M11_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
M11_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_middle,
                      Comedy_AIns_middle, Comedy_MPFC_middle) 
M11_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_middle,
                      Horror_AIns_middle, Horror_MPFC_middle) 

# Define middle variables. 
All_NAcc_offset <- AllSubs_NeuralActivation$NAcc_offset
All_AIns_offset <- AllSubs_NeuralActivation$AIns_offset
All_MPFC_offset <- AllSubs_NeuralActivation$MPFC_offset

Comedy_NAcc_offset <- AllSubs_NeuralActivation_Comedy$NAcc_offset
Comedy_AIns_offset <- AllSubs_NeuralActivation_Comedy$AIns_offset
Comedy_MPFC_offset <- AllSubs_NeuralActivation_Comedy$MPFC_offset

Horror_NAcc_offset <- AllSubs_NeuralActivation_Horror$NAcc_offset
Horror_AIns_offset <- AllSubs_NeuralActivation_Horror$AIns_offset
Horror_MPFC_offset <- AllSubs_NeuralActivation_Horror$MPFC_offset

# Define models. 
M12_df <- data.frame(All_NAcc_offset, All_AIns_offset, All_MPFC_offset) 
M12_C_df <- data.frame(Comedy_NAcc_offset, Comedy_AIns_offset, Comedy_MPFC_offset) 
M12_H_df <- data.frame(Horror_NAcc_offset, Horror_AIns_offset, Horror_MPFC_offset) 

M13_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_offset, All_AIns_offset, All_MPFC_offset) 
M13_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_offset,
                      Comedy_AIns_offset, Comedy_MPFC_offset) 
M13_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_offset,
                      Horror_AIns_offset, Horror_MPFC_offset) 

M14_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_middle, All_MPFC_offset) 
M14_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_onset,
                      Comedy_AIns_middle, Comedy_MPFC_offset) 
M14_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_onset,
                      Horror_AIns_middle, Horror_MPFC_offset) 

Neuroforecasting: First Week US.

M1: Behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    Type:scale(Theaters_US_W1_num), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-1.55922 -0.28515  0.02387  0.33475  1.38066 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           16.4641     0.2010  81.928  < 2e-16 ***
Typecomedy                            -0.5646     0.2655  -2.127  0.04310 *  
scale(Theaters_US_W1_num)              1.5282     0.4206   3.633  0.00121 ** 
Typecomedy:scale(Theaters_US_W1_num)  -0.3868     0.4422  -0.875  0.38980    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.688 on 26 degrees of freedom
Multiple R-squared:  0.7944,    Adjusted R-squared:  0.7706 
F-statistic: 33.48 on 3 and 26 DF,  p-value: 4.425e-09

Warning: 'r.squaredGLMM' now calculates a revised statistic. See the help page.

           R2m       R2c
[1,] 0.7759523 0.7759523
[1] 68.40126

M2: Affective data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + Type:scale(Pos_arousal_scaled) + 
    Type:scale(Neg_arousal_scaled), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.2384 -0.4609  0.1408  0.9003  1.9665 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           16.8747     1.0683  15.795 3.51e-14 ***
Typecomedy                            -0.4244     1.7881  -0.237    0.814    
scale(Pos_arousal_scaled)             -0.2925     0.8104  -0.361    0.721    
scale(Neg_arousal_scaled)             -0.3368     0.7708  -0.437    0.666    
Typecomedy:scale(Pos_arousal_scaled)   0.5651     0.9104   0.621    0.541    
Typecomedy:scale(Neg_arousal_scaled)   1.4148     1.8204   0.777    0.445    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.433 on 24 degrees of freedom
Multiple R-squared:  0.1762,    Adjusted R-squared:  0.004619 
F-statistic: 1.027 on 5 and 24 DF,  p-value: 0.4242

           R2m       R2c
[1,] 0.1504214 0.1504214
[1] 114.0345

M3: Aggregate and affective data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + Type:scale(Pos_arousal_scaled) + 
    Type:scale(Neg_arousal_scaled), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.2384 -0.4609  0.1408  0.9003  1.9665 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           16.8747     1.0683  15.795 3.51e-14 ***
Typecomedy                            -0.4244     1.7881  -0.237    0.814    
scale(Pos_arousal_scaled)             -0.2925     0.8104  -0.361    0.721    
scale(Neg_arousal_scaled)             -0.3368     0.7708  -0.437    0.666    
Typecomedy:scale(Pos_arousal_scaled)   0.5651     0.9104   0.621    0.541    
Typecomedy:scale(Neg_arousal_scaled)   1.4148     1.8204   0.777    0.445    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.433 on 24 degrees of freedom
Multiple R-squared:  0.1762,    Adjusted R-squared:  0.004619 
F-statistic: 1.027 on 5 and 24 DF,  p-value: 0.4242

           R2m       R2c
[1,] 0.1504214 0.1504214
[1] 114.0345

M4: ISC data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_ISC) + 
    scale(AIns_ISC) + scale(MPFC_ISC) + Type:scale(NAcc_ISC) + 
    Type:scale(AIns_ISC) + Type:scale(MPFC_ISC), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.1237 -0.1968  0.1923  0.5385  2.0713 

Coefficients:
                           Estimate Std. Error t value Pr(>|t|)    
(Intercept)                 16.5637     0.4020  41.204   <2e-16 ***
Typecomedy                  -0.9115     0.5418  -1.682    0.107    
scale(NAcc_ISC)              0.9324     0.5941   1.569    0.131    
scale(AIns_ISC)             -0.3689     0.3931  -0.938    0.358    
scale(MPFC_ISC)              0.4294     0.5914   0.726    0.475    
Typecomedy:scale(NAcc_ISC)  -0.8986     0.6960  -1.291    0.210    
Typecomedy:scale(AIns_ISC)   0.8286     0.6768   1.224    0.234    
Typecomedy:scale(MPFC_ISC)  -0.5130     0.6906  -0.743    0.465    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.397 on 22 degrees of freedom
Multiple R-squared:  0.2824,    Adjusted R-squared:  0.05403 
F-statistic: 1.237 on 7 and 22 DF,  p-value: 0.3255

           R2m       R2c
[1,] 0.2298773 0.2298773
[1] 113.8967

M5: ISC data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_ISC) + 
    scale(AIns_ISC) + scale(MPFC_ISC) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_ISC) + Type:scale(AIns_ISC) + Type:scale(MPFC_ISC), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.98531 -0.20166 -0.04314  0.23676  0.91728 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.27469    0.45499  35.769  < 2e-16 ***
Typecomedy                            1.61430    0.75287   2.144  0.04772 *  
scale(Theaters_US_W1_num)             1.15042    0.42760   2.690  0.01609 *  
scale(Pos_arousal_scaled)            -0.58249    0.31185  -1.868  0.08020 .  
scale(Neg_arousal_scaled)            -0.35399    0.32465  -1.090  0.29170    
scale(NAcc_ISC)                       0.43093    0.28961   1.488  0.15620    
scale(AIns_ISC)                      -0.32368    0.15176  -2.133  0.04878 *  
scale(MPFC_ISC)                       0.59958    0.23959   2.503  0.02355 *  
Typecomedy:scale(Theaters_US_W1_num)  0.07361    0.44304   0.166  0.87012    
Typecomedy:scale(Pos_arousal_scaled)  0.37749    0.37850   0.997  0.33345    
Typecomedy:scale(Neg_arousal_scaled)  2.58403    0.77428   3.337  0.00418 ** 
Typecomedy:scale(NAcc_ISC)           -0.07078    0.34349  -0.206  0.83934    
Typecomedy:scale(AIns_ISC)            0.32735    0.30424   1.076  0.29791    
Typecomedy:scale(MPFC_ISC)           -1.01402    0.28517  -3.556  0.00263 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5284 on 16 degrees of freedom
Multiple R-squared:  0.9254,    Adjusted R-squared:  0.8647 
F-statistic: 15.26 on 13 and 16 DF,  p-value: 1.316e-06

           R2m       R2c
[1,] 0.8724403 0.8724403
[1] 58.00076

M6: Neural whole data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_whole) + 
    scale(AIns_whole) + scale(MPFC_whole) + Type:scale(NAcc_whole) + 
    Type:scale(AIns_whole) + Type:scale(MPFC_whole), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.4915 -0.2204  0.2896  0.7418  1.8031 

Coefficients:
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.5914     0.5222  31.772   <2e-16 ***
Typecomedy                    -0.7600     0.7486  -1.015    0.321    
scale(NAcc_whole)             -0.4432     0.4705  -0.942    0.356    
scale(AIns_whole)              0.3810     0.5583   0.682    0.502    
scale(MPFC_whole)              0.1363     0.4951   0.275    0.786    
Typecomedy:scale(NAcc_whole)   0.5601     0.6453   0.868    0.395    
Typecomedy:scale(AIns_whole)  -0.2261     0.8750  -0.258    0.799    
Typecomedy:scale(MPFC_whole)   0.3771     0.6121   0.616    0.544    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.414 on 22 degrees of freedom
Multiple R-squared:  0.2644,    Adjusted R-squared:  0.03039 
F-statistic:  1.13 on 7 and 22 DF,  p-value: 0.3806

           R2m       R2c
[1,] 0.2142805 0.2142805
[1] 114.6373

M7: Neural whole data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_whole) + 
    scale(AIns_whole) + scale(MPFC_whole) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_whole) + Type:scale(AIns_whole) + Type:scale(MPFC_whole), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-1.02273 -0.35033  0.07729  0.34019  0.76672 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.11709    0.51212  31.471 8.07e-16 ***
Typecomedy                            1.64239    0.84223   1.950 0.068917 .  
scale(Theaters_US_W1_num)             1.58506    0.38938   4.071 0.000889 ***
scale(Pos_arousal_scaled)            -0.41897    0.50218  -0.834 0.416401    
scale(Neg_arousal_scaled)            -0.20949    0.36568  -0.573 0.574682    
scale(NAcc_whole)                    -0.13854    0.21155  -0.655 0.521866    
scale(AIns_whole)                     0.37182    0.23953   1.552 0.140142    
scale(MPFC_whole)                     0.05455    0.30009   0.182 0.858031    
Typecomedy:scale(Theaters_US_W1_num) -0.46033    0.40783  -1.129 0.275650    
Typecomedy:scale(Pos_arousal_scaled)  0.36503    0.53729   0.679 0.506599    
Typecomedy:scale(Neg_arousal_scaled)  2.46587    0.87658   2.813 0.012500 *  
Typecomedy:scale(NAcc_whole)          0.58983    0.30656   1.924 0.072324 .  
Typecomedy:scale(AIns_whole)         -0.66356    0.38887  -1.706 0.107267    
Typecomedy:scale(MPFC_whole)          0.22726    0.34040   0.668 0.513881    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5818 on 16 degrees of freedom
Multiple R-squared:  0.9095,    Adjusted R-squared:  0.836 
F-statistic: 12.37 on 13 and 16 DF,  p-value: 5.649e-06

           R2m       R2c
[1,] 0.8472102 0.8472102
[1] 63.77717

M8: Neural onset data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_onset) + 
    scale(AIns_onset) + scale(MPFC_onset) + Type:scale(NAcc_onset) + 
    Type:scale(AIns_onset) + Type:scale(MPFC_onset), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.5300 -0.5105  0.2008  0.8999  1.6313 

Coefficients:
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.9165     0.4348  38.909   <2e-16 ***
Typecomedy                    -1.5640     0.5839  -2.679   0.0137 *  
scale(NAcc_onset)             -0.3704     0.4673  -0.793   0.4364    
scale(AIns_onset)             -0.2755     0.5514  -0.500   0.6223    
scale(MPFC_onset)              0.1515     0.4799   0.316   0.7553    
Typecomedy:scale(NAcc_onset)   0.6038     0.6123   0.986   0.3348    
Typecomedy:scale(AIns_onset)  -0.6671     0.7697  -0.867   0.3955    
Typecomedy:scale(MPFC_onset)   0.8616     0.6876   1.253   0.2234    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.372 on 22 degrees of freedom
Multiple R-squared:  0.3076,    Adjusted R-squared:  0.08725 
F-statistic: 1.396 on 7 and 22 DF,  p-value: 0.2564

          R2m      R2c
[1,] 0.252038 0.252038
[1] 112.8243

M9: Neural onset data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_onset) + 
    scale(AIns_onset) + scale(MPFC_onset) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_onset) + Type:scale(AIns_onset) + Type:scale(MPFC_onset), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.96803 -0.24681  0.03351  0.25574  1.20131 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           16.9886     0.7413  22.916 1.16e-13 ***
Typecomedy                             0.1394     1.1114   0.125  0.90176    
scale(Theaters_US_W1_num)              1.4962     0.4274   3.501  0.00296 ** 
scale(Pos_arousal_scaled)             -0.6039     0.4841  -1.248  0.23014    
scale(Neg_arousal_scaled)             -0.6697     0.4872  -1.375  0.18820    
scale(NAcc_onset)                     -0.2375     0.2314  -1.026  0.31999    
scale(AIns_onset)                     -0.6850     0.3559  -1.924  0.07226 .  
scale(MPFC_onset)                      0.3377     0.2831   1.193  0.25035    
Typecomedy:scale(Theaters_US_W1_num)  -0.3545     0.4530  -0.783  0.44527    
Typecomedy:scale(Pos_arousal_scaled)   0.4258     0.5389   0.790  0.44101    
Typecomedy:scale(Neg_arousal_scaled)   2.0833     1.0155   2.052  0.05695 .  
Typecomedy:scale(NAcc_onset)           0.4585     0.3466   1.323  0.20450    
Typecomedy:scale(AIns_onset)           0.3619     0.4625   0.783  0.44534    
Typecomedy:scale(MPFC_onset)          -0.2351     0.3957  -0.594  0.56077    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6723 on 16 degrees of freedom
Multiple R-squared:  0.8791,    Adjusted R-squared:  0.7809 
F-statistic: 8.952 on 13 and 16 DF,  p-value: 4.861e-05

           R2m       R2c
[1,] 0.8005177 0.8005177
[1] 72.45883

M10: Neural middle data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_middle) + 
    scale(AIns_middle) + scale(MPFC_middle) + Type:scale(NAcc_middle) + 
    Type:scale(AIns_middle) + Type:scale(MPFC_middle), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.9911 -0.2988  0.0050  0.7515  1.7656 

Coefficients:
                              Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.77011    0.46119  36.363   <2e-16 ***
Typecomedy                    -0.50114    0.63772  -0.786    0.440    
scale(NAcc_middle)            -0.23549    0.52413  -0.449    0.658    
scale(AIns_middle)             0.09539    0.45152   0.211    0.835    
scale(MPFC_middle)            -0.22490    0.40314  -0.558    0.583    
Typecomedy:scale(NAcc_middle)  0.25363    0.65298   0.388    0.701    
Typecomedy:scale(AIns_middle)  0.97835    0.72105   1.357    0.189    
Typecomedy:scale(MPFC_middle)  0.01243    0.59223   0.021    0.983    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.379 on 22 degrees of freedom
Multiple R-squared:  0.3008,    Adjusted R-squared:  0.07838 
F-statistic: 1.352 on 7 and 22 DF,  p-value: 0.2739

           R2m       R2c
[1,] 0.2460959 0.2460959
[1] 113.1143

M11: Neural middle data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_middle) + 
    scale(AIns_middle) + scale(MPFC_middle) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_middle) + Type:scale(AIns_middle) + Type:scale(MPFC_middle), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-1.10322 -0.36840  0.00993  0.29978  0.85947 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.24078    0.53535  30.337 1.44e-15 ***
Typecomedy                            0.56119    0.86413   0.649  0.52528    
scale(Theaters_US_W1_num)             1.94258    0.48827   3.979  0.00108 ** 
scale(Pos_arousal_scaled)            -0.32424    0.39569  -0.819  0.42458    
scale(Neg_arousal_scaled)            -0.36038    0.39905  -0.903  0.37986    
scale(NAcc_middle)                    0.35385    0.31498   1.123  0.27783    
scale(AIns_middle)                    0.28451    0.22197   1.282  0.21820    
scale(MPFC_middle)                   -0.03603    0.19816  -0.182  0.85800    
Typecomedy:scale(Theaters_US_W1_num) -0.79231    0.50911  -1.556  0.13920    
Typecomedy:scale(Pos_arousal_scaled)  0.13061    0.46377   0.282  0.78184    
Typecomedy:scale(Neg_arousal_scaled)  1.07341    0.98610   1.089  0.29248    
Typecomedy:scale(NAcc_middle)        -0.04651    0.36743  -0.127  0.90084    
Typecomedy:scale(AIns_middle)        -0.07177    0.44303  -0.162  0.87334    
Typecomedy:scale(MPFC_middle)        -0.15072    0.30186  -0.499  0.62435    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6526 on 16 degrees of freedom
Multiple R-squared:  0.8861,    Adjusted R-squared:  0.7936 
F-statistic: 9.576 on 13 and 16 DF,  p-value: 3.136e-05

           R2m       R2c
[1,] 0.8110669 0.8110669
[1] 70.67346

M12: Neural offset data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_offset) + 
    scale(AIns_offset) + scale(MPFC_offset) + Type:scale(NAcc_offset) + 
    Type:scale(AIns_offset) + Type:scale(MPFC_offset), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.6391 -0.2826  0.1857  0.4832  1.9697 

Coefficients:
                              Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.66144    0.42293  39.395   <2e-16 ***
Typecomedy                    -1.13736    0.60189  -1.890   0.0721 .  
scale(NAcc_offset)            -0.23257    0.43893  -0.530   0.6015    
scale(AIns_offset)             0.20575    0.40019   0.514   0.6123    
scale(MPFC_offset)             0.34238    0.60171   0.569   0.5751    
Typecomedy:scale(NAcc_offset)  0.09242    0.70091   0.132   0.8963    
Typecomedy:scale(AIns_offset) -0.75863    0.75061  -1.011   0.3232    
Typecomedy:scale(MPFC_offset)  0.06412    0.71789   0.089   0.9296    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.461 on 22 degrees of freedom
Multiple R-squared:  0.2158,    Adjusted R-squared:  -0.03376 
F-statistic: 0.8647 on 7 and 22 DF,  p-value: 0.5487

           R2m       R2c
[1,] 0.1726791 0.1726791
[1] 116.5591

M13: Neural offset data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_offset) + 
    scale(AIns_offset) + scale(MPFC_offset) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_offset) + Type:scale(AIns_offset) + Type:scale(MPFC_offset), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.95826 -0.19004  0.01735  0.28270  0.82240 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.54157    0.46986  35.205  < 2e-16 ***
Typecomedy                            0.64195    0.71756   0.895  0.38425    
scale(Theaters_US_W1_num)             1.73641    0.43905   3.955  0.00113 ** 
scale(Pos_arousal_scaled)            -0.21965    0.39299  -0.559  0.58396    
scale(Neg_arousal_scaled)            -0.42213    0.40015  -1.055  0.30713    
scale(NAcc_offset)                   -0.10641    0.16521  -0.644  0.52862    
scale(AIns_offset)                    0.35726    0.17661   2.023  0.06013 .  
scale(MPFC_offset)                   -0.15255    0.34416  -0.443  0.66351    
Typecomedy:scale(Theaters_US_W1_num) -0.54995    0.45317  -1.214  0.24252    
Typecomedy:scale(Pos_arousal_scaled)  0.40384    0.42856   0.942  0.36004    
Typecomedy:scale(Neg_arousal_scaled)  2.01190    0.76190   2.641  0.01781 *  
Typecomedy:scale(NAcc_offset)         0.07303    0.26125   0.280  0.78342    
Typecomedy:scale(AIns_offset)        -0.31226    0.30741  -1.016  0.32484    
Typecomedy:scale(MPFC_offset)         0.64035    0.37431   1.711  0.10644    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5311 on 16 degrees of freedom
Multiple R-squared:  0.9246,    Adjusted R-squared:  0.8633 
F-statistic: 15.09 on 13 and 16 DF,  p-value: 1.425e-06

           R2m       R2c
[1,] 0.8711766 0.8711766
[1] 58.31452

M14: Sequence model

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_onset) + 
    scale(AIns_middle) + scale(MPFC_offset) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_onset) + Type:scale(AIns_middle) + Type:scale(MPFC_offset), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.62622 -0.15641  0.01399  0.18986  0.55821 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.48753    0.37099  44.442  < 2e-16 ***
Typecomedy                            1.22484    0.62330   1.965  0.06701 .  
scale(Theaters_US_W1_num)             1.20661    0.44658   2.702  0.01571 *  
scale(Pos_arousal_scaled)            -0.36656    0.30473  -1.203  0.24652    
scale(Neg_arousal_scaled)            -0.49434    0.31825  -1.553  0.13990    
scale(NAcc_onset)                    -0.56862    0.21519  -2.642  0.01774 *  
scale(AIns_middle)                    0.48879    0.14626   3.342  0.00414 ** 
scale(MPFC_offset)                    0.45785    0.38556   1.187  0.25237    
Typecomedy:scale(Theaters_US_W1_num) -0.04290    0.45553  -0.094  0.92614    
Typecomedy:scale(Pos_arousal_scaled)  0.43353    0.34719   1.249  0.22974    
Typecomedy:scale(Neg_arousal_scaled)  2.56520    0.68599   3.739  0.00179 ** 
Typecomedy:scale(NAcc_onset)          0.82616    0.25085   3.293  0.00458 ** 
Typecomedy:scale(AIns_middle)        -0.42378    0.24584  -1.724  0.10401    
Typecomedy:scale(MPFC_offset)         0.08557    0.40050   0.214  0.83351    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4157 on 16 degrees of freedom
Multiple R-squared:  0.9538,    Adjusted R-squared:  0.9162 
F-statistic:  25.4 on 13 and 16 DF,  p-value: 3.284e-08

           R2m       R2c
[1,] 0.9192794 0.9192794
[1] 43.61224